Sajid LHESSANI

Created and scaled a full-stack educational platform focused on algorithmic trading and AI, reaching over 5,000 students across 113 countries. Authored more than 30 published articles and developed a YouTube channel with over 500k views on algorithmic trading topics.

Successfully launched a physical business in Bali, Indonesia, and managed its sale in May 2025. Oversaw the hiring and management of a diverse team of 6 employees, including both French and Indonesian staff.

Co-founded and successfully scaled a regulated hedge fund with $80M AUM, specializing in AI-based trading strategies. Developed proprietary ML-driven trading strategies for crypto and FX markets, and built scalable cloud infrastructure on AWS for live model deployment.

Designed and deployed AI trading bots on FTX and Binance, managing $5M AUM and achieving $40M in monthly volume. Developed AWS-based risk analytics and portfolio engines for clients in Dubai and Mexico, and built market-making bots and real-time arbitrage detection systems.

Delivered Python-based analytics solutions for Tier-1 banking clients in the UK and EU, developing stress testing models and cash-flow simulations for regulatory compliance. Directed the end-to-end development of a Monte Carlo engine for credit risk exposure and constructed dashboards using Power BI and Tableau.

Built data visualization and statistical models for banking clients, supporting the development and testing of statistical models (PD, LGD, EAD) for major UK banks. Utilized SQL and Python for data cleaning, transformation, and analysis of large datasets, and created automated data validation scripts.

Automated FX risk reports using Python, implementing Monte Carlo and stochastic models to replace legacy Excel tools. Built custom dashboards using internal BNP tools for risk leadership and advised team leads on transitioning analytics stack from Excel to Python.

Conducted regression and classification model comparisons, including logistic, SVM, and Random Forest, to model real-world consumer behavior. Delivered a predictive analytics toolkit using R for internal business teams and presented insights on customer segmentation and attrition risk to senior managers.

Led a $190K R&D program focused on studying durability indicators for offshore viaduct concrete, building statistical models to assess long-term material performance. Presented findings to international engineers for certification and validation, and managed interdisciplinary teams and vendor budgets.

Acquired theoretical and practical knowledge in calculation and design for major civil engineering structures and buildings, mastering modern tools for numerical simulation. Focused on modeling and design of structures in prestressed concrete, composite materials, wood, and reinforced concrete, including exceptional engineering structures like dams and nuclear cooling towers.

Specialized in market strategy, international finance, and business analytics. Led team projects on market competitiveness analysis and sales forecasting, applying Excel, Power BI, and Python for real-world business case studies. Completed electives focused on digital transformation and data-driven decision-making.